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Brain-Computer Interfaces using Machine Learning

Theodoros Papadopoulos, Iraklis Varlamis
2019 Zenodo  
In the theoretical part, we overview the underlying principles of Brain-Computer Interface systems, as well as, different approaches for the interpretation and the classification of brain signals.  ...  This thesis explores machine learning models for the analysis and classification of electroencephalographic (EEG) signals used in Brain-Computer Interface (BCI) systems.  ...  Brain-Computer Interfaces Human-computer interaction (HCI) is a research field focused on the interfaces between people (users) and computers. Humans interact with computers in many ways.  ... 
doi:10.5281/zenodo.2581620 fatcat:n65zuruy2feibh2pa24d2ekr2i

Visual and Auditory Brain–Computer Interfaces

Shangkai Gao, Yijun Wang, Xiaorong Gao, Bo Hong
2014 IEEE Transactions on Biomedical Engineering  
Over the past several decades, electroencephalogram (EEG)-based brain-computer interfaces (BCIs) have attracted attention from researchers in the field of neuroscience, neural engineering, and clinical  ...  Index Terms-brain-computer interface (BCI), visual BCI, auditory BCI, multiple access Manuscript  ...  Historical review The term "brain-computer interface" first appeared in 1970s.  ... 
doi:10.1109/tbme.2014.2300164 pmid:24759277 fatcat:nu2c3xa2nne2xg6oahfi3ykqxy

A functional source separation algorithm to enhance error-related potentials monitoring in noninvasive brain-computer interface

Francesco Ferracuti, Valentina Casadei, Ilaria Marcantoni, Sabrina Iarlori, Laura Burattini, Andrea Monteriù, Camillo Porcaro
2020 Computer Methods and Programs in Biomedicine  
It has been shown that ErrPs can be automatically detected with time-discrete feedback tasks, which are widely applied in the Brain-Computer Interface (BCI) field for error correction or adaptation.  ...  The proposed FSS-based method increases the single-trial detection accuracy of ErrPs with respect to both single channel (Cz, FCz) and xDAWN spatial filter.  ...  Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.  ... 
doi:10.1016/j.cmpb.2020.105419 pmid:32151908 fatcat:7k6rwurkmrd57j3gnoaw2xfceu

Brain computer interfacing: Applications and challenges

Sarah N. Abdulkader, Ayman Atia, Mostafa-Sami M. Mostafa
2015 Egyptian Informatics Journal  
Brain computer interface technology represents a highly growing field of research with application systems.  ...  We also discuss major usability and technical challenges that face brain signals utilization in various components of BCI system.  ...  ICA accomplishes spatial filtering in an unsupervised manner by decomposing the observed EEG into statistically independent components (ICs).  ... 
doi:10.1016/j.eij.2015.06.002 fatcat:iiopgu4eqfekrc6ombyjy6sk2y

Brain-Computer Interface: Advancement and Challenges

M F Mridha, Sujoy Chandra Das, Muhammad Mohsin Kabir, Aklima Akter Lima, Md Rashedul Islam, Yutaka Watanobe
2021 Sensors  
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain based on neuroscience, signal processing, biomedical sensors, hardware, etc.  ...  In addition, a brief overview of the technologies or hardware, mostly sensors used in BCI, is appended.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21175746 pmid:34502636 pmcid:PMC8433803 fatcat:gt5v46mr5nhjvptosklmvq2ria

Best practice for single-trial detection of event-related potentials: Application to brain-computer interfaces

Hubert Cecotti, Anthony J. Ries
2017 International Journal of Psychophysiology  
The detection of event-related potentials (ERPs) in the electroencephalogram (EEG) signal is a fundamental component in non-invasive brain-computer interface (BCI) research, and in modern cognitive neuroscience  ...  Efficient single-trial detection techniques require processing steps that include temporal filtering, spatial filtering, and classification.  ...  The rank of the sensors is displayed for each subject in Fig. 12 . Discussion Single-trial detection of ERPs in EEG/MEG signals is a key element in brain-computer interface systems.  ... 
doi:10.1016/j.ijpsycho.2016.07.500 pmid:27453051 fatcat:n3j5xo5zrvhsdfnwme4ebriyei

Subject Combination and Electrode Selection in Cooperative Brain-Computer Interface Based on Event Related Potentials

Hubert Cecotti, Bertrand Rivet
2014 Brain Sciences  
New paradigms are required in Brain-Computer Interface (BCI) systems for the needs and expectations of healthy people.  ...  Hence, four types of BCI can be distinguished: 1. The classical BCI: it involves a single person and a single brain modality, i.e., a single type of brain response (ERP or SSVEP, motor imagery, ...)  ...  Keywords: Brain-Computer Interface; cooperative mode; event-related potentials (ERP); electrode selection Introduction The field of non-invasive Brain-Computer Interface (BCI) has been particularly active  ... 
doi:10.3390/brainsci4020335 pmid:24961765 pmcid:PMC4101481 fatcat:nrxdooyxbjek3buee7crcuilv4

Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review

Marco Congedo, Alexandre Barachant, Rajendra Bhatia
2017 Brain-Computer Interfaces  
An EEG-based Brain-Computer Interface (BCI) is a system for translating EEG signals directly into commands for a computerized system.  ...  brain signals into commands and an interface, the computerized application, whose ultimate goal is performing actions while giving continuous feedback to the user about its operation.  ... 
doi:10.1080/2326263x.2017.1297192 fatcat:zxlvqa7eh5cttnclne6pgcbyqy

An automated and fast approach to detect single-trial visual evoked potentials with application to brain–computer interface

Yiheng Tu, Yeung Sam Hung, Li Hu, Gan Huang, Yong Hu, Zhiguo Zhang
2014 Clinical Neurophysiology  
The proposed approach can obtain robust and reliable visual evoked potentials in an automated and fast manner, thus satisfying the requirements of practical brain-computer interface systems.  ...  and high-performance brain-computer interface (BCI) system.  ...  LH is supported by National Natural Science Foundation of China (No. 81271685). All authors have no conflict of interest.  ... 
doi:10.1016/j.clinph.2014.03.028 pmid:24794514 fatcat:5gmumbvdkvgfvkgsxkwyfocami

Learning From EEG Error-Related Potentials in Noninvasive Brain-Computer Interfaces

R Chavarriaga, José del R. Millán
2010 IEEE transactions on neural systems and rehabilitation engineering  
In this approach, single trial detection of error-related electroencephalography (EEG) potentials is used to infer the optimal agent behavior by decreasing the probability of agent decisions that elicited  ...  We describe error-related potentials generated while a human user monitors the performance of an external agent and discuss their use for a new type of brain-computer interaction.  ...  ERROR-BASED LEARNING IN BRAIN-COMPUTER INTERACTION Given the possibility of detecting error-related potentials in single trial, we want to explore next whether this information can be exploited to infer  ... 
doi:10.1109/tnsre.2010.2053387 pmid:20570777 fatcat:7fn2bewpszagheu7cafbbh7abu

The brain–computer interface cycle

Marcel van Gerven, Jason Farquhar, Rebecca Schaefer, Rutger Vlek, Jeroen Geuze, Anton Nijholt, Nick Ramsey, Pim Haselager, Louis Vuurpijl, Stan Gielen, Peter Desain
2009 Journal of Neural Engineering  
Brain-computer interfaces (BCIs) have attracted much attention recently, triggered by new scientific progress in understanding brain function and by impressive applications.  ...  The aim of this review is to give an overview of the various steps in the BCI cycle, i.e., the loop from the measurement of brain activity, classification of data, feedback to the subject and the effect  ...  Acknowledgments The authors gratefully acknowledge the support of the BrainGain Smart Mix Programme of the Netherlands Ministry of Economic Affairs and the Netherlands Ministry of Education, Culture and  ... 
doi:10.1088/1741-2560/6/4/041001 pmid:19622847 fatcat:772bjatjxvbs7oxlkbpyvsn7be

Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016 [article]

Dongrui Wu and Yifan Xu and Bao-Liang Lu
2020 arXiv   pre-print
A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals.  ...  This paper reviews journal publications on TL approaches in EEG-based BCIs in the last few years, i.e., since 2016.  ...  INTRODUCTION A brain-computer interface (BCI) enables a user to communicate with a computer using his/her brain signals directly [1] , [2] .  ... 
arXiv:2004.06286v4 fatcat:e32dqag5pvha7mzabrwead2hni

User-centered design in brain–computer interfaces—A case study

Martijn Schreuder, Angela Riccio, Monica Risetti, Sven Dähne, Andrew Ramsay, John Williamson, Donatella Mattia, Michael Tangermann
2013 Artificial Intelligence in Medicine  
Keywords: Brain-computer interface Event-related potentials Auditory evoked potentials Linear discriminant analysis User-centered design Assistive technology Stroke Traumatic brain injury Locked-in syndrome  ...  a b s t r a c t Objective: The array of available brain-computer interface (BCI) paradigms has continued to grow, and so has the corresponding set of machine learning methods which are at the core of  ...  This paper only reflects the authors' views and funding agencies are not liable for any use that may be made of the information contained herein.  ... 
doi:10.1016/j.artmed.2013.07.005 pmid:24076341 fatcat:mjs2sbg6vzfnneglmbidmw7rxa

Brain Computer Interfaces, a Review

Luis Fernando Nicolas-Alonso, Jaime Gomez-Gil
2012 Sensors  
Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity.  ...  A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices.  ...  Acknowledgements This work was partially supported by the regional 2010 Research Project Plan of the Junta de Castilla y León, (Spain), under project VA034A10-2.  ... 
doi:10.3390/s120201211 pmid:22438708 pmcid:PMC3304110 fatcat:rinslsoovba4hizv3ugwdy6g2e

The Berlin Brain-Computer Interface: Progress Beyond Communication and Control

Benjamin Blankertz, Laura Acqualagna, Sven Dähne, Stefan Haufe, Matthias Schultze-Kraft, Irene Sturm, Marija Ušćumlic, Markus A. Wenzel, Gabriel Curio, Klaus-Robert Müller
2016 Frontiers in Neuroscience  
While we assume we are still a long way away from integrating Brain-Computer Interface (BCI) technology in general interaction with computers, or from implementing neurotechnological measures in safety-critical  ...  The combined effect of fundamental results about neurocognitive processes and advancements in decoding mental states from ongoing brain signals has brought forth a whole range of potential neurotechnological  ...  ACKNOWLEDGMENTS We acknowledge inspiring and fruitful discussions with many researchers, with whom we discussed novel applications of BCI technology and advanced data analysis methods.  ... 
doi:10.3389/fnins.2016.00530 pmid:27917107 pmcid:PMC5116473 fatcat:noknjgpzm5hlxbbe43g42wvyci
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